Have you been in situations where your students lack knowledge on how to present and analyze data but your course contents are so packed that there’s no extra time to teach or elaborate further on how to use statistical tools? Yet, data analysis skills should not be overlooked, as it plays an important role across many disciplines.
The case of SCNC1111
The Science Foundation Course SCNC1111 Scientific Method and Reasoning encountered this situation. As part of their group project, the students of SCNC1111 have to make their own investigations into how Mathematics and Statistics can be or have been applied to daily life and scientific inquiry. Over the past years, the teaching team observed that while most students were good at data collection, some of them seemed to be at a loss on what to do with the data: What can the data help us to do?
Seeing that some students lack proper training in handling, interpreting or analyzing data, the SCNC1111 teaching team found it essential to fill the gap:
As a result, several useful and efficient instructional videos have been developed on how to use free online resources to plot nice graphs and do basic statistical analysis. Students’ skills and learning experience can both be enhanced. With the hope to incorporate students into the process of teaching, the SCNC1111 teaching team has previously recruited senior undergraduates as Senior Tutors for the course and one of the Senior Tutors, Mr. Dag Wong, was in charge of the video production. The team believes that “students can be our resourceful partner in developing high quality teaching materials and videos.”
Interdisciplinary resource-sharing
These videos can prove to be useful not only in science, but also in different disciplines such as economics, psychology, engineering, sociology, to name a few. In the long run, such productions can initiate synergy among different faculties in developing and sharing educational resources in common areas of inquiry. As students are expected to learn a wide spectrum of skills, creation and utilization of interdisciplinary materials will be highly beneficial.
Here are some typical data analysis questions asked by students across the campus, to which the SCNC1111 team has responded through the videos. Please feel free to share these links with your students!
What if I have an equation and I simply want to plot a nice-looking graph?
What if I have gathered some data and I wonder if there is any relationship between them?
How does regression work?
How does linear regression work with excel?
Let this be a start to knowledge sharing across disciplines!
Contact us if you are interested to learn more.